Exploring the nexus between hydroclimatic variability, population growth, land use land cover change, and long-term upper Nyong Basin River chemistry (Central Africa rainforest).

Hydrological and hydrogeochemical functioning of rivers depends on the relationship between climatic variability, land use and land cover change (LULCC), and population dynamics. However, there is a scientific gap on this relationship in the humid tropical zone of Central Africa. This study aims to fill this gap by examining the link between hydroclimatic variability, population growth, LULCC, and river water chemistry in the upper Nyong basin (UNB). Atmospheric temperature and rainfall data were obtained from Climatic Research Unit gridded Time Series 4.07 (CRU TS 4.07), in Google Earth Pro 7 software. Demographic data were obtained by projection based on the 1976, 1987 and 2005 censuses, assuming population increase as in the past. Land use and land cover (LULC) maps for 2005-2020 periods were produced from Landsat images (Landsat 7 ETM + from 2005 to 2010 and Landsat 8 OLI from 2015 to 2020). Supervised classification with Maximum Likelihood Algorithm was used to classify the Landsat images in ArcGIS 10.8 Software. Three LULC classes (Forest, impervious and agricultural surface and water) were successfully classified, with overall accuracies from 96.4 to 100%, and Kappa coefficients from 88.4 to 100%. The study also used 29-year (1994-2023) meteorological (rainfall), hydrological (discharge) and hydrochemical (water temperature [WT], pH, electrical conductivity (EC), alkalinity [Alk], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], dissolved organic carbon [DOC], silica [[Formula: see text]] and suspended particulate matter [SPM]) database provided by Multiscale TROPIcal CatchmentS critical zone observatory (M-TROPICS CZO) in the UNB. The results show that population increased in UNB from 2.6 million to 4.1 million between 2005 and 2020. This population growth has increased demands for food, housing, agricultural activities, etc. To meet these demands, the populations have converted 1,207 [Formula: see text] of forest into impervious and agricultural surface (buildings, roads, agricultural land, etc.). More so, LULC classes have evolved from 2005 to 2020 as follows: 17,845 [Formula: see text] to 16,638 [Formula: see text] (-6.7%) for forest, 1,376 [Formula: see text] to 2,587 [Formula: see text] (+ 88%) for impervious and agricultural surface, and 15 [Formula: see text] to 11 [Formula: see text] (-26.7%) for water. The increase in impervious and agricultural surface has led to increase in soil sealing, thus promoting increase runoff and, long term discharge. Despite the increase in discharge, a significant increase (p < 0.01) in pH, EC, TDS, cation and [Formula: see text] concentrations were observed. This increase was attributed to the discharge of household and industrial waste and wastewater into the environment and river, and probably due to a greater contribution of groundwater to surface water. The groundwater contribution was supported by the significant decrease (p < 0.01) in DOC over the long term. In addition, the significant decrease in [Formula: see text], [Formula: see text], Alk, [Formula: see text], and [Formula: see text] is associated with increased photosynthetic activity due to eutrophication of the Nyong River, as well as the long term soil depletion of these chemical elements by slash-and-burn agriculture.